Optimal design of engine mount using an artificial life algorithm

When designing fluid mounts, design parameters can be varied in order to obtain a desired notch frequency and notch depth. The notch frequency is a function of the mount parameters and is typically selected by the designer to occur at the vibration disturbance frequency. Since the process of choosing these parameters can involve some trial and error, it seems to be a great application for obtaining optimal performance of the mount. Many combinations of parameters are possible to give us the desired notch frequency, but the question is which combination provides the lowest depth? Therefore, an automatic optimal technique is needed to optimize the fluid mount.In this study, the enhanced artificial life algorithm (EALA) is applied to minimizing transmissibility of a fluid mount at the desired notch frequency, and at the notch and resonant frequencies. The present hybrid algorithm is the synthesis of a conventional artificial life algorithm with the random tabu search (R-tabu) method and then, the time for searching optimal solution could be reduced from the conventional artificial life algorithm and its solution accuracy became better.The results show that the performance of the optimized mount by using the hybrid algorithm has been better than that of the conventional fluid mount.